turicreate.image_analysis.resize¶

turicreate.image_analysis.resize(image, width, height, channels=None, decode=False, resample='nearest')¶

Resizes the image or SArray of Images to a specific width, height, and number of channels.

Parameters:

image : turicreate.Image | SArray

The image or SArray of images to be resized.

width : int

The width the image is resized to.

height : int

The height the image is resized to.

channels : int, optional

The number of channels the image is resized to. 1 channel corresponds to grayscale, 3 channels corresponds to RGB, and 4 channels corresponds to RGBA images.

decode : bool, optional

Whether to store the resized image in decoded format. Decoded takes more space, but makes the resize and future operations on the image faster.

resample : ‘nearest’ or ‘bilinear’

Specify the resampling filter:

'nearest': Nearest neigbhor, extremely fast

'bilinear': Bilinear, fast and with less aliasing artifacts

Returns:

out : turicreate.Image: Returns a resized Image object.

Notes

Grayscale Images -> Images with one channel, representing a scale from white to black

RGB Images -> Images with 3 channels, with each pixel having Green, Red, and Blue values.

RGBA Images -> An RGB image with an opacity channel.

Examples

Resize a single image

>>> img = turicreate.Image('https://static.turi.com/datasets/images/sample.jpg')
>>> resized_img = turicreate.image_analysis.resize(img,100,100,1)

Resize an SArray of images

>>> url ='https://static.turi.com/datasets/images/nested'
>>> image_sframe = turicreate.image_analysis.load_images(url, "auto", with_path=False,
...                                                    recursive=True)
>>> image_sarray = image_sframe["image"]
>>> resized_images = turicreate.image_analysis.resize(image_sarray, 100, 100, 1)